{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "from copy import copy\n",
    "import os\n",
    "import numpy as np\n",
    "import re\n",
    "\n",
    "from pandas import ExcelWriter\n",
    "from pandas import ExcelFile\n",
    "from numpy import savetxt\n",
    "from bs4 import BeautifulSoup\n",
    "import requests\n",
    "\n",
    "import openpyxl\n",
    "import xlrd\n",
    "\n",
    "from collections import Counter\n",
    "\n",
    "'''For visualization'''\n",
    "import bokeh.models as bm, bokeh.plotting as pl\n",
    "from bokeh.models import Legend\n",
    "from bokeh.io import output_notebook\n",
    "from bokeh.plotting import ColumnDataSource, figure, output_file, show\n",
    "from bokeh.transform import factor_cmap\n",
    "import plotly\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# AMOUNT OF WOMEN-MEN IN ESTAFETA SECTION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_estafeta = pd.read_excel('./Popular_Film_data/Estafeta.xlsx', engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_gender_per_issue = df_estafeta[['Issue No.', 'Sex']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/pandas/core/frame.py:4110: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().drop(\n"
     ]
    }
   ],
   "source": [
    "for index, row in df_gender_per_issue.iterrows():\n",
    "    if isinstance(row['Issue No.'], int) == False:\n",
    "        df_gender_per_issue.drop(index, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "for index, row in df_gender_per_issue.iterrows():\n",
    "    if row['Sex'] == '?':\n",
    "        df_gender_per_issue.drop(index, inplace=True)\n",
    "    if row['Sex'] == ' ?':\n",
    "        df_gender_per_issue.drop(index, inplace=True)\n",
    "    if row['Sex'] == '?.':\n",
    "        df_gender_per_issue.drop(index, inplace=True)\n",
    "    if row['Sex'] == '? ':\n",
    "        df_gender_per_issue.drop(index, inplace=True)    \n",
    "    if row['Sex'] == 'F?':\n",
    "        df_gender_per_issue.drop(index, inplace=True)\n",
    "    if row['Sex'] == 'M?':\n",
    "        df_gender_per_issue.drop(index, inplace=True)\n",
    "    if row['Sex'] == 'M & M':\n",
    "        df_gender_per_issue.drop(index, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Issue No.</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sex</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>754</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Issue No.\n",
       "Sex           \n",
       "F          152\n",
       "M          754"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gender_per_issue = df_gender_per_issue.dropna(subset=['Issue No.', 'Sex'])  \n",
    "df_gender_per_issue.groupby(\"Sex\").count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "articles_2_sex_distribution = {}\n",
    "for uniq_article in df_gender_per_issue['Issue No.'].unique():\n",
    "    articles_2_sex_distribution[uniq_article] = Counter(df_gender_per_issue['Sex'][df_gender_per_issue['Issue No.'] == uniq_article])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_gender = pd.DataFrame(articles_2_sex_distribution, columns = list(articles_2_sex_distribution.keys())).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "men = []\n",
    "women = []\n",
    "for index, row in df_gender.iterrows():\n",
    "    if index == 'M':\n",
    "        men = list(row)\n",
    "    if index == 'F':\n",
    "        women = list(row)\n",
    "\n",
    "issues_number = list(articles_2_sex_distribution.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 4320x1800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"font.family\"] = \"Times New Roman\" \n",
    "plt.rcParams[\"font.style\"] = \"normal\"\n",
    "\n",
    "font_path = '/System/Library/Fonts/Supplemental/Times New Roman.ttf'\n",
    "\n",
    "fig = plt.figure(figsize=(60,25))\n",
    "\n",
    "\n",
    "plt.bar(np.arange(0, len(issues_number)) - 0.2, men, width=0.4, color='firebrick')\n",
    "plt.bar(np.arange(0, len(issues_number)) + 0.2, women, width= 0.4, label='Women', color = 'steelblue')\n",
    "plt.style.use('ggplot')\n",
    "plt.xticks(np.arange(0, len(issues_number)),issues_number[::1], fontsize=30, rotation = 90)\n",
    "plt.yticks(range(0, 65, 5), fontsize=30)\n",
    "\n",
    "blue_patch = mpatches.Patch(color='steelblue', label='women')\n",
    "red_patch =  mpatches.Patch(color='firebrick', label='men')\n",
    "plt.legend(handles=[red_patch, blue_patch], loc='upper right', prop={\"size\":50})\n",
    "\n",
    "plt.xlabel('Issue No.', fontsize=35)\n",
    "plt.ylabel('Number of letters per issue', fontsize=35)\n",
    "plt.title(\"Distribution of fan mail, by gender, in $\\it{Popular}$ $\\it{Film’}$s Estafeta\", size=50)\n",
    "\n",
    "#os.mkdir(\"./Visualizations\")\n",
    "#plt.savefig('./Visualizations/Distribution_of_fan_mail_by_gender.pdf', bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PHOTO CONTEST"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preparation of Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(240, 11)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_photos = pd.read_excel('./Popular_Film_data/Photo_contest.xlsx', engine='openpyxl')\n",
    "df_photos.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_photos = df_photos.drop(columns=['Hobbies', 'Comments'])\n",
    "df_photos = df_photos.drop(columns=['Unnamed: 7', 'Unnamed: 8', 'Unnamed: 9', 'Unnamed: 10'])\n",
    "df_photos['Month'] = [month.strip() for month in df_photos['Month']]\n",
    "m={\n",
    "    'Jan': 1, \n",
    "    'Feb': 2, \n",
    "    'March': 3, \n",
    "    'April': 4,\n",
    "    'May': 5, \n",
    "    'June': 6,\n",
    "    'July': 7,\n",
    "    'Aug': 8,\n",
    "    'Sep': 9,\n",
    "    'Oct': 10,\n",
    "    'Nov': 11,\n",
    "    'Dec': 12\n",
    "} \n",
    "df_photos.Month = df_photos.Month.map(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Issue No.</th>\n",
       "      <th>Day</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Nombre de concursante</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>Date_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17</td>\n",
       "      <td>25</td>\n",
       "      <td>11</td>\n",
       "      <td>1926</td>\n",
       "      <td>Manuel Bernal de los Santos</td>\n",
       "      <td>M</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1926-11-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>1926</td>\n",
       "      <td>Bernardino Alonso del Olmo</td>\n",
       "      <td>M</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1926-12-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>1926</td>\n",
       "      <td>Juan Faidella Jufré</td>\n",
       "      <td>M</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1926-12-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>1926</td>\n",
       "      <td>Juan Alfredo Ulrich</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1926-12-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>1926</td>\n",
       "      <td>Maria Samaniego</td>\n",
       "      <td>F</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1926-12-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1927</td>\n",
       "      <td>Máximo Arraiz</td>\n",
       "      <td>M</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1927-06-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1927</td>\n",
       "      <td>Félix Bailo Escanilla</td>\n",
       "      <td>M</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1927-06-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1927</td>\n",
       "      <td>Jacinto Martínez</td>\n",
       "      <td>M</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1927-06-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1927</td>\n",
       "      <td>Antonio Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1927-06-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1927</td>\n",
       "      <td>José Martín Cordero</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1927-06-02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>240 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Issue No.  Day  Month  Year        Nombre de concursante Sex   Age  \\\n",
       "0           17   25     11  1926  Manuel Bernal de los Santos   M  12.0   \n",
       "1           18    2     12  1926   Bernardino Alonso del Olmo   M  14.0   \n",
       "2           20   16     12  1926          Juan Faidella Jufré   M  18.0   \n",
       "3           21   23     12  1926          Juan Alfredo Ulrich   M  20.0   \n",
       "4           21   23     12  1926             Maria Samaniego    F  10.0   \n",
       "..         ...  ...    ...   ...                          ...  ..   ...   \n",
       "235         44    2      6  1927                Máximo Arraiz   M  19.0   \n",
       "236         44    2      6  1927        Félix Bailo Escanilla   M  17.0   \n",
       "237         44    2      6  1927            Jacinto Martínez    M  19.0   \n",
       "238         44    2      6  1927            Antonio Rodriguez   M  29.0   \n",
       "239         44    2      6  1927          José Martín Cordero   M  21.0   \n",
       "\n",
       "     Date_time  \n",
       "0   1926-11-25  \n",
       "1   1926-12-02  \n",
       "2   1926-12-16  \n",
       "3   1926-12-23  \n",
       "4   1926-12-23  \n",
       "..         ...  \n",
       "235 1927-06-02  \n",
       "236 1927-06-02  \n",
       "237 1927-06-02  \n",
       "238 1927-06-02  \n",
       "239 1927-06-02  \n",
       "\n",
       "[240 rows x 8 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_datetime(df_photos[[\"Year\", \"Month\", \"Day\"]])\n",
    "df_photos['Date_time'] = pd.to_datetime(df_photos[[\"Year\", \"Month\", \"Day\"]])\n",
    "df_photos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distribution of contestants, by gender, with No. of issue on the X Axis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_gender = df_photos[['Issue No.', 'Sex']]\n",
    "for index, row in df_gender.iterrows():\n",
    "    if isinstance(row['Issue No.'], int) == False:\n",
    "        df_gender.drop(index, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "articles_2_sex_distribution = {}\n",
    "for uniq_article in df_gender['Issue No.'].unique():\n",
    "    articles_2_sex_distribution[uniq_article] = Counter(df_gender['Sex'][df_gender['Issue No.'] == uniq_article])\n",
    "df_gender = pd.DataFrame(articles_2_sex_distribution, columns = list(articles_2_sex_distribution.keys())).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "men = []\n",
    "women = []\n",
    "for index, row in df_gender.iterrows():\n",
    "    if index == 'M':\n",
    "        men = list(row)\n",
    "    if index == 'F':\n",
    "        women = list(row)\n",
    "\n",
    "issues_number = list(articles_2_sex_distribution.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of male contestants:  196.0\n",
      "Number of female contestants:  44.0\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of male contestants: \", sum(men))\n",
    "print(\"Number of female contestants: \", sum(women))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 4680x1800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"font.family\"] = \"Times New Roman\" \n",
    "plt.rcParams[\"font.style\"] = \"normal\"\n",
    "\n",
    "fig = plt.figure(figsize=(65,25))\n",
    "\n",
    "\n",
    "plt.bar(np.arange(0, len(issues_number)) + 0.2, men, width=0.4, color='firebrick')\n",
    "plt.bar(np.arange(0, len(issues_number)) - 0.2, women, width= 0.4, color = 'steelblue')\n",
    "\n",
    "plt.style.use('ggplot')\n",
    "plt.xticks(np.arange(0, len(issues_number)), issues_number[::1], fontsize=30)\n",
    "plt.yticks(range(0, 20, 1), fontsize=30)\n",
    "\n",
    "red_patch = mpatches.Patch(color='firebrick', label='men')\n",
    "blue_patch =  mpatches.Patch(color='steelblue', label='women')\n",
    "plt.legend(handles=[red_patch, blue_patch], loc='upper right', prop={\"size\":50})\n",
    "\n",
    "\n",
    "plt.xlabel('Issue No.', fontsize=35)\n",
    "plt.ylabel('Number of entry ballots published', fontsize=35)\n",
    "plt.title(\"Distribution of contestants, by gender, of $\\it{Popular}$ $\\it{Film’}$s reader contest, \\n $\\it{¿Tengo}$ $\\it{condiciones}$ $\\it{de}$ $\\it{ser}$ $\\it{artista?}$\", fontsize = 50)\n",
    "\n",
    "\n",
    "#plt.savefig('./Visualizations/Distribution_of_contestants_by_gender_issue.pdf', bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distribution of contestants, by age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "aging = dict(Counter(df_photos[df_photos['Sex'] == \"M\"]['Age']))\n",
    "myKeys = list(aging.keys())\n",
    "myKeys.sort()\n",
    "aging = {i: aging[i] for i in myKeys}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of female contestants:  44\n",
      "Number of male contestants:  196\n",
      "Total contestants:  240\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of female contestants: \", sum(dict(Counter(df_photos[df_photos['Sex'] == \"F\"]['Age'])).values()))\n",
    "print(\"Number of male contestants: \", sum(dict(Counter(df_photos[df_photos['Sex'] == \"M\"]['Age'])).values()))\n",
    "print(\"Total contestants: \", sum ([44, 196]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of male contestants from 14 to 22 [not including] y.o.:  160.0\n"
     ]
    }
   ],
   "source": [
    "m = 14\n",
    "s = 21\n",
    "summation = 0.\n",
    "while m <= s:\n",
    "    summation += aging[m]\n",
    "    m += 1\n",
    "print(\"Number of male contestants from 14 to 22 [not including] y.o.: \", summation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"font.family\"] = \"Times New Roman\" \n",
    "plt.rcParams[\"font.style\"] = \"normal\"\n",
    "\n",
    "fig = plt.figure(figsize=(20, 10))\n",
    "plt.style.use('ggplot')\n",
    "counts, bins, bars = plt.hist(df_photos[df_photos['Sex'] == \"M\"]['Age'], bins=10, color='forestgreen')\n",
    "\n",
    "legend_dict = {}\n",
    "bins = [round(x) for x in list(bins)]\n",
    "for i in range(len(bins)-1):\n",
    "    string = str(bins[i]) + '-' + str(bins[i+1])\n",
    "    legend_dict[string] = counts[i]\n",
    "    \n",
    "labels_age = [str(key) + ' = ' + str(int(value)) for key, value in legend_dict.items()]\n",
    "\n",
    "\n",
    "plt.title(\"Distribution of male contestants, by age, of $\\it{Popular}$ $\\it{Film’}$s reader contest, \\n $\\it{¿Tengo}$ $\\it{condiciones}$ $\\it{de}$ $\\it{ser}$ $\\it{artista}$$\\it{?}$\", fontsize=24)\n",
    "plt.ylabel('Number of entry ballots', fontsize=20)\n",
    "plt.xlabel('Age of contestants', fontsize=20)\n",
    "\n",
    "plt.legend(handles=(bars),\n",
    "           labels=(labels_age),\n",
    "           title=\"Age = Entries\", title_fontsize=16,\n",
    "           scatterpoints=1,\n",
    "           bbox_to_anchor=(1, 0.7), loc=2, borderaxespad=1.,\n",
    "           ncol=1,\n",
    "           fontsize=14)\n",
    "\n",
    "plt.xticks(range(1, 50, 1), fontsize=14)\n",
    "plt.yticks(range(0,int(max(list(legend_dict.values()))),5), fontsize=14)\n",
    "plt.tight_layout()\n",
    "\n",
    "\n",
    "#plt.savefig('./Visualizations/Distribution_of_male_contestants_by_age.pdf', bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DATA FOR A MAP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/pandas/core/frame.py:4110: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().drop(\n"
     ]
    }
   ],
   "source": [
    "place_df = df_estafeta[['Place']]\n",
    "\n",
    "for index, row in place_df.iterrows():\n",
    "    if isinstance(row['Place'], str) == False:\n",
    "        place_df.drop(index, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cities = dict(Counter(place_df['Place']))\n",
    "cities_df = pd.DataFrame.from_dict({'City' : list(cities.keys()), 'Count':list(cities.values()), \n",
    "                                    'Latitude':'', 'Longitude': ''})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "for index, row in cities_df.iterrows():\n",
    "    response = requests.get(url=\"https://en.wikipedia.org/wiki/{}\".format(row['City']))\n",
    "    response.encoding = 'utf8'\n",
    "    html = response.text\n",
    "    soup = BeautifulSoup(html)\n",
    "    \n",
    "    if soup.find(\"span\", {\"class\": \"latitude\"}):\n",
    "        latitude = soup.find(\"span\", {\"class\": \"latitude\"}).text\n",
    "        cities_df.at[index,'Latitude'] = latitude\n",
    "    else:\n",
    "        cities_df.at[index,'Latitude'] = np.nan\n",
    "        \n",
    "    if soup.find(\"span\", {\"class\": \"longitude\"}):\n",
    "        longitude = soup.find(\"span\", {\"class\": \"longitude\"}).text\n",
    "        cities_df.at[index,'Longitude'] = longitude\n",
    "    else:\n",
    "        cities_df.at[index,'Longitude'] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "for index, row in cities_df.iterrows():\n",
    "    if row['Count']<=3:\n",
    "        cities_df.at[index,'Weight'] = 10\n",
    "        cities_df.at[index,'Comment'] = 'Weight = 10, letters < 3'\n",
    "\n",
    "    if 3<row['Count']<=6:\n",
    "        cities_df.at[index,'Weight'] = 15\n",
    "        cities_df.at[index,'Comment'] = 'Weight = 15, letters 3 ~ 6'\n",
    "\n",
    "    if 6<row['Count']<=12:\n",
    "        cities_df.at[index,'Weight'] = 20\n",
    "        cities_df.at[index,'Comment'] = 'Weight = 20, letters 6 ~ 12'\n",
    "\n",
    "    if 12<row['Count']<=24:\n",
    "        cities_df.at[index,'Weight'] = 25\n",
    "        cities_df.at[index,'Comment'] = 'Weight = 25, letters 12 ~ 24'\n",
    "\n",
    "    if 24<row['Count']<=48:\n",
    "        cities_df.at[index,'Weight'] = 30\n",
    "        cities_df.at[index,'Comment'] = 'Weight = 30, letters 24 ~ 48'\n",
    "\n",
    "    if row['Count']>48:\n",
    "        cities_df.at[index,'Weight'] = 35\n",
    "        cities_df.at[index,'Comment'] = 'Weight = 35, letters > 48'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "cities_df.to_csv('./Popular_Film_data/Coordinates_to_finish_manually.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NETWORK OF HOBBIES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sports_1</th>\n",
       "      <th>Sports_2</th>\n",
       "      <th>Sports_3</th>\n",
       "      <th>Sports_4</th>\n",
       "      <th>Sports_5</th>\n",
       "      <th>Sport_6</th>\n",
       "      <th>Sport_7</th>\n",
       "      <th>Knowledge/Hobby 1</th>\n",
       "      <th>Knowledge/Hobby 2</th>\n",
       "      <th>Knowledge/Hobby 3</th>\n",
       "      <th>Knoweldge/Hobby 4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>soccer</td>\n",
       "      <td>Basque pelota</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Education</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>not listed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>soccer</td>\n",
       "      <td>swimming</td>\n",
       "      <td>horse riding</td>\n",
       "      <td>boxing</td>\n",
       "      <td>jump</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>physical exercise/gymnastics</td>\n",
       "      <td>swimming</td>\n",
       "      <td>basketball</td>\n",
       "      <td>boxing</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>theater</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>swimming</td>\n",
       "      <td>horse riding</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Sports_1       Sports_2      Sports_3 Sports_4   \\\n",
       "0                        soccer  Basque pelota           NaN       NaN   \n",
       "1                    not listed            NaN           NaN       NaN   \n",
       "2                        soccer       swimming  horse riding    boxing   \n",
       "3  physical exercise/gymnastics       swimming    basketball    boxing   \n",
       "4                      swimming   horse riding           NaN       NaN   \n",
       "\n",
       "  Sports_5 Sport_6  Sport_7 Knowledge/Hobby 1  Knowledge/Hobby 2   \\\n",
       "0      NaN      NaN     NaN          Education                NaN   \n",
       "1      NaN      NaN     NaN                NaN                NaN   \n",
       "2     jump      NaN     NaN                NaN                NaN   \n",
       "3      NaN      NaN     NaN            theater                NaN   \n",
       "4      NaN      NaN     NaN                NaN                NaN   \n",
       "\n",
       "  Knowledge/Hobby 3 Knoweldge/Hobby 4  \n",
       "0               NaN               NaN  \n",
       "1               NaN               NaN  \n",
       "2               NaN               NaN  \n",
       "3               NaN               NaN  \n",
       "4               NaN               NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_hobbies = pd.read_excel('./Popular_Film_data/Photo_contest.xlsx', sheet_name=3, engine='openpyxl')\n",
    "df = df_hobbies.loc[:, \"Sports_1\":]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_hobbies = []\n",
    "for row in df.values:\n",
    "    row = [x.strip().capitalize() for x in row if str(x) != 'nan']\n",
    "    all_hobbies.append(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "general_hobbies = []\n",
    "for hobby in all_hobbies:\n",
    "    for h in hobby:\n",
    "        general_hobbies.append(h)\n",
    "general_hobbies = Counter(general_hobbies)\n",
    "\n",
    "sorted_general_hobbies = sorted(general_hobbies.items(), key=lambda x:x[1], reverse=True)\n",
    "general_hobbies = dict(sorted_general_hobbies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"font.family\"] = \"Times New Roman\" \n",
    "plt.rcParams[\"font.style\"] = \"normal\"\n",
    "\n",
    "names = list(general_hobbies.keys())\n",
    "values = list(general_hobbies.values())\n",
    "fig = plt.figure(figsize=(20,20))\n",
    "\n",
    "plt.barh(range(len(general_hobbies)), values, tick_label=names)\n",
    "\n",
    "plt.xticks(fontsize=30)\n",
    "plt.yticks(fontsize=20)\n",
    "\n",
    "plt.xlabel('Number of people', fontsize=35)\n",
    "plt.ylabel('Hobbies', fontsize=35)\n",
    "plt.title(\"List of all hobbies of $\\it{Popular}$ $\\it{Film’}$s male contestants\", fontsize = 45)\n",
    "\n",
    "#plt.savefig('./Visualizations/All_hobbies.pdf', bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "lists_of_hobbies = []\n",
    "for row in df.values:\n",
    "    row = [x.strip().capitalize() for x in row if str(x) != 'nan']\n",
    "    lists_of_hobbies += row\n",
    "    \n",
    "unique_hobbies = list(np.unique(lists_of_hobbies))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "pair_entrances_df = pd.DataFrame(columns=unique_hobbies, index=unique_hobbies)\n",
    "\n",
    "for name1 in unique_hobbies:\n",
    "    for name2 in unique_hobbies:\n",
    "        num_people_with_pair = np.sum([{name1, name2}.issubset(set(lst)) for lst in all_hobbies])\n",
    "        pair_entrances_df.at[name1, name2] = num_people_with_pair"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Acrobatics</th>\n",
       "      <th>Arabic</th>\n",
       "      <th>Baseball</th>\n",
       "      <th>Basketball</th>\n",
       "      <th>Basque pelota</th>\n",
       "      <th>Bicycling</th>\n",
       "      <th>Boxing</th>\n",
       "      <th>Bullfighting</th>\n",
       "      <th>Car racing/driving</th>\n",
       "      <th>Cinematography</th>\n",
       "      <th>...</th>\n",
       "      <th>Sciences</th>\n",
       "      <th>Skating</th>\n",
       "      <th>Soccer</th>\n",
       "      <th>Stenography</th>\n",
       "      <th>Swimming</th>\n",
       "      <th>Tennis</th>\n",
       "      <th>Theater</th>\n",
       "      <th>Track &amp; field</th>\n",
       "      <th>Veterinary science</th>\n",
       "      <th>Wood carving</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Acrobatics</th>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>Arabic</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>Baseball</th>\n",
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       "      <td>...</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>Basketball</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Basque pelota</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 51 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Acrobatics Arabic Baseball Basketball Basque pelota Bicycling  \\\n",
       "Acrobatics             1      0        0          0             0         1   \n",
       "Arabic                 0      1        0          0             0         0   \n",
       "Baseball               0      0        1          0             0         0   \n",
       "Basketball             0      0        0          1             0         0   \n",
       "Basque pelota          0      0        0          0             7         1   \n",
       "\n",
       "              Boxing Bullfighting Car racing/driving Cinematography  ...  \\\n",
       "Acrobatics         1            0                  0              0  ...   \n",
       "Arabic             0            0                  0              0  ...   \n",
       "Baseball           1            0                  0              0  ...   \n",
       "Basketball         1            0                  0              0  ...   \n",
       "Basque pelota      2            0                  2              0  ...   \n",
       "\n",
       "              Sciences Skating Soccer Stenography Swimming Tennis Theater  \\\n",
       "Acrobatics           0       0      0           0        0      0       0   \n",
       "Arabic               0       0      0           0        1      0       0   \n",
       "Baseball             0       0      0           0        1      1       0   \n",
       "Basketball           0       0      0           0        1      0       1   \n",
       "Basque pelota        0       1      7           0        4      0       0   \n",
       "\n",
       "              Track & field Veterinary science Wood carving  \n",
       "Acrobatics                0                  0            0  \n",
       "Arabic                    1                  0            0  \n",
       "Baseball                  1                  0            0  \n",
       "Basketball                0                  0            0  \n",
       "Basque pelota             0                  0            0  \n",
       "\n",
       "[5 rows x 51 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pair_entrances_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def table_2_3column(table, to_dataframe=True):\n",
    "    new_table = []\n",
    "    names = table.columns\n",
    "    for i in range(len(table)):\n",
    "        for j in range(i, len(table)):\n",
    "            if table.iloc[i, j] != 0:\n",
    "                new_table.append([names[i], names[j], table.iloc[i, j]])\n",
    "    if to_dataframe:\n",
    "        return pd.DataFrame(new_table, columns=('Source', 'Target', 'Weight'))\n",
    "    return new_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Source</th>\n",
       "      <th>Target</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acrobatics</td>\n",
       "      <td>Bicycling</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Acrobatics</td>\n",
       "      <td>Boxing</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Arabic</td>\n",
       "      <td>French</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Arabic</td>\n",
       "      <td>Horse riding</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Arabic</td>\n",
       "      <td>Swimming</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>Stenography</td>\n",
       "      <td>Track &amp; field</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>Swimming</td>\n",
       "      <td>Tennis</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Swimming</td>\n",
       "      <td>Theater</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>Swimming</td>\n",
       "      <td>Track &amp; field</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>Tennis</td>\n",
       "      <td>Track &amp; field</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>234 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Source         Target  Weight\n",
       "0     Acrobatics      Bicycling       1\n",
       "1     Acrobatics         Boxing       1\n",
       "2         Arabic         French       1\n",
       "3         Arabic   Horse riding       1\n",
       "4         Arabic       Swimming       1\n",
       "..           ...            ...     ...\n",
       "229  Stenography  Track & field       1\n",
       "230     Swimming         Tennis       4\n",
       "231     Swimming        Theater       1\n",
       "232     Swimming  Track & field      11\n",
       "233       Tennis  Track & field       2\n",
       "\n",
       "[234 rows x 3 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_table_hobbies = table_2_3column(pair_entrances_df, to_dataframe=True)\n",
    "\n",
    "for index, row in final_table_hobbies.iterrows():\n",
    "    if row['Source'] == row['Target']:\n",
    "        final_table_hobbies.drop(index, inplace=True)\n",
    "        \n",
    "final_table_hobbies.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_table_hobbies.to_csv(\"./Popular_Film_data/Hobbies_network.csv\", index=False)"
   ]
  }
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